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The need to prioritize maintenance activities and investments based on asset criticality and associated risk is seen increasingly as important in industry. However, proper use of criticality in developing maintenance strategies and plans is still at a nascent stage in most organisations. A review of industrial practices showed that criticality is considered as more or less a static quantity that is not updated with sufficient frequency as the operating environment changes. This paper examines an electricity distribution network operator (DNO) to show the need to model the changing nature of criticality and ensure an optimal maintenance strategy and plan, aligned to business needs. A Real-time Criticality Based Maintenance (DCBM) methodology is proposed to identify factors affecting and influencing changes to criticality, monitor and update asset criticality and exploit the dynamic criticality to optimise maintenance decisions. Asset criticality was calculated using network performance, safety, environmental integrity, maintenance cost among other factors as the consequence categories for asset failure. The criticality for each asset (such as transformer circuit breakers, busbars etc.) is calculated as a weighted sum of the impact of supply loss on each of the consequence categories. Variations in some factors such as electricity demand influences changes in asset criticality with time and therefore criticality is modelled as a dynamic process, which is a function of time in addition to other factors. A comparison between an existing and a reviewed maintenance plan is shown where there are considerable variations in criticality over time. The performance measure used for the maintenance plan is based on the utility network reliability (quality of service) which is measured in terms of Customer Interruptions (CI) and Customer Minutes Lost (CML). The performance targets (for CIs & CMLs) and standard service levels for DNOs are given in the UK's Office of Gas and Electricity Markets (OFGEM). The result showed improvement in availability mainly due to reduction of the duration of scheduled outages and short interruptions. .